Python

Innostem Edunce Edlabs has developed a course syllabus for Python which covers all the core concepts of Python. The curriculum also includes training on advance libraries such as NumPy, Matplotlib, Dictionaries and Pandas with Django frameworks and introduction to Data Science.

Course objectives

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Python has become one of the top influencing programming languages in recent years. Python is also an object-oriented programming language which supports a wide range of application development which includes software applications, computation, scientific data analysis, web development, etc. Applications are faster and simpler to develop using Python. Like Java, Python can also be used to develop any kind of Software irrespective of device, domain and platform.

Python Course Curriculum

Introduction
Python Object and Data Structure Basics
  • Introduction to Python Data Types
  • Numbers
  • Variables Assignment
  • Introduction Strings
  • Indexing and Slicing with strings
  • String properties and Methods
  • Print Formatting with strings
  • List in python
  • Dictionaries in python
  • Tuples with python
  • Sets in python
  • Booleans in python
  • I/O basics files in python
Python Comparison Operators
  • Comparison Operators in python
Statements
  • If elif and else statement in python 20. For loops in python
  • while loops in python
  • List comprehension
  • Methods and functions
  • Lambda Expression, Map and Filter Functions
  • Nested Statements and scope
Object Oriented Programming
  • Introduction to object oriented programming language
  • Attributes and Class Keyword
  • Class Object Attribute
  • Inheritance and polymorphism
  • __name__ and __main__
  • Modules and packages
  • Errors and exceptional handling
  • Python Decorators
  • Python Generators
  • Python Lists
  • List of list
  • Subsetting List 38. Slicing and dicing
Introduction To Data Science
  • Subsetting list of lists 40. List manipulations
  • Inner working of list
  • Functions and packages 43. import package
  • Selective import
  • Different ways of importing
  • Introduction to numpy 47. Numpy side effects
  • Subsetting Numpy Arrays 49. 2D Numpy arrays
Numpy
  • Subsetting 2D Numpy Arrays 51. 2D Arithmetic
  • Numpy: Basic Statistics
  • Average versus median
Matplotlib
  • Basic plots with matplotlib
  • Line Plot
  • Line Plot: Interpretation 57. Scatter Plot
  • Histogram
  • Build Histogram: bins
  • Build Histogram: compare 61. Labels
  • Ticks
  • Sizes
  • Colors
Dictionaries and Pandas
  • Introduction
  • Creation, Access dictionaries
  • Dictionary Manipulation
  • Pandas
  • Dictionary to to Data Frame
  • CSV to Data Frame
  • Pandas Part 2
  • Introduction to Django
  • Use of Django
  • URL’s
  • View
  • Model
  • Templates
  • Sending request to view 79. Handling the request 80. Creation of Data models
Django
  • Quering Data
  • Path() function
  • Creating Models
  • Activating Models
  • Creating an admin user
  • Writing simple form
  • Customization in admin panel
  • Style sheet

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